Reflection from bound microbubbles at high ultrasound frequencies
Bibliographic record
Abstract
Targeted contrast agents and ultrasound imaging are now used in combination for the assessment and tracking of biomarkers in animal models in vivo. These applications have triggered interest in the understanding and prediction of the ultrasound echoes from contrast agents attached to cells. This study describes the reflection enhancement due to microbubbles bound on a gelatin surface. The reflection enhancement was measured using ultrasound pulses at high frequency (40 MHz) and low pressure (38 kPa peak-negativepressure) allowing a linear approximation to be applied. The observed reflection coefficient increased with the number of microbubbles, until reaching saturation at 0.9 when the surface coverage fraction was 35%. A multiple scattering model assuming that the targeted microbubbles are confined within an infinitesimally thin layer appeared suitable in predicting the reflection coefficient even at very high surface densities. These results could permit the optimization of the sensitivity of highfrequency ultrasound to targeted contrast agents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".